The North Atlantic Oscillation (NAO) is one of the
major modes of variability of the Northern Hemisphere atmosphere. It is
a large scale see-saw in atmospheric mass between the subtropical high
and the polar low exerting a strong control on winter climate in Europe,
North America, and Northern Asia. The NAO index is defined as the normalized
pressure difference between stations on the Azores and Iceland.

A positive NAO index indicates a stronger than usual
subtropical high pressure center and a deeper than normal Icelandic low.
The increased pressure difference results in more and stronger winter storms
crossing the Atlantic Ocean on a more northerly track. This results in
warm and wet winters in Europe and cold and dry winters in Greenland and
Northern Canada, while the eastern United States experiences mild and wet
winter conditions. A negative NAO index points to a weak subtropical high
and a weak Icelandic low. The reduced pressure gradient results in fewer
and weaker winter storms crossing mostly on west-east paths bringing moist
air into the Mediterranean and cold air to Northern Europe. The east cost
of the United States gets more cold air and snow while Greenland enjoys
mild winters (Hurrell, 1995 ).

After ENSO, the NAO is one of the most dominant modes
of global climate variability. Like El Niño, La Niña, and
the Southern Oscillation, it is considered a free internal oscillation
of the climate system not subjected to external forcing. It is shown, however,
that it is closely linked to energetic solar eruptions. Surprisingly, it
turns out that features of solar activity that have been shown to be related
to El Niños and La Niñas
(Landscheidt, 1999 a, 2000 a), also have an impact on
the NAO.

Fig.1 shows a close correlation between extrema in
the Southern Oscillation Index (SOI), indicating
ENSO events, and special phases a and d within the ascending
and the declining part of the 11-year sunspot cycle. The SOI data are reversed
so that strong positive peaks point to El Niños and troughs to La
Niñas. The 11-year cycle is not symmetric. Reliable observations
available since 1750 show that the mean rise to the sunspot maximum (4.3
years) is considerably steeper than the decline to the sunspot minimum
(6.7 years). The mean ratio of the rising
part to the whole 11-year cycle is 0.39.

Nature often repeats patterns and connected functions
on different scales. The phases indicated in Fig.1 by triangles represent
such fractals. Yellow triangles mark points a and d which
divide the ascending and the descending part of the sunspot cycle such
that the ratio 0.39, found in the whole cycle, is again established in
the respective parts. It should be noted that point 0.39 in the 11-year
cycle coincides with the sunspot maximum, a climax of activity. Points
a and d seem to have a similar function. Midpoints between
phases a and d(a/d and d/a),
marked by blue triangles, are farthest away from points a and d.
So it is consistent that they indicate the opposite effect. After
1970, on the right of the two arrows labelled PTC
(Perturbation in torque cycle), all yellow triangles point to El
Niños and all blue triangles to La Niñas. Before 1970, everything
is reversed. As this conspicuous pattern is linked to the Sun's activity,
which again is based on the Sun's dynamics, an explanation of the phase
reversal, too, should be found in the Sun's dynamics. I have shown that
there are torque cycles in the Sun's oscillation about the center of mass
of the solar system which are associated with solar activity (Landscheidt,
1986 a, b, 1999 b ) and climate change (Landscheidt,
1983, 1987, 1988, 1990, 1995, 1998 a,b, 2000 c ).

On this basis, I correctly predicted energetic solar
eruptions, strong geomagnetic storms, weaker solar activity past 1990,
the end of the Sahelian drought, extrema in global temperature anomalies,
drought conditions in the United States, and the last two El Niños
1 to 4 years before the events. The forecast of solar eruptions and geomagnetic
storms, checked by astronomers and the Space Environment Center, Boulder,
covered six years and achieved a hit rate of 90 %.

Fig. 2 shows that the rate of change of the Sun's
orbital angular momentum (L) - the torque dL/dt driving the Sun's motion
about the center of mass of the solar system - forms a torque cycle of
varying length. The initial phases of this cycle are marked by blue circles.
Perturbations in the sinusoidal course of the torque cycle, indicated by
arrows, occurred around 1933.6 and 1968.8. Such events recur at quasi-periodic
intervals and mark initial phases of a perturbation cycle of 35.8 years.
Observation shows that such predictable perturbations release phase reversals
and other disturbances in cycles of climate phenomena connected with the
Sun's activity (Landscheidt, 1995,
1998 a, b). The perturbation in the torque cycle that
occurred around 1968 falls just at the phase reversal in the correlation
pattern presented in Fig.1.

Fig 3 shows why just phases a and d
within the ascending and the descending part of the 11-year sunspot cycle
could be related to ENSO events. It shows the distribution of highly energetic
X-ray flares within the respective parts of the sunspot
cycle. The sample
covers all X-class flares equal to or greater than 6 observed by satellites
between 1970 and 2000. These data are available at the National Geophysical
Data Center, Boulder. The rising and falling parts of different length
were normalized to have equal length 1. Then they were superimposed to
make it easy to recognize identical phases. Intense X-ray flares, nearly
always accompanied by heavy coronal mass ejections, are geophysically more
effective than flares categorized into classes of optical brightness (Joselyn,
1986). As many as 19 of the 34 investigated X-ray flares
concentrate on the short interval of 0.23 on the unit scale, marked by
a horizontal bar at the top left. Only 15 of the flares fall at the remaining
large interval covering a range of 0.77 on the unit scale. The normalized
position of a and d is marked by a brown triangle. The climate
effect, observed at a and d, lags the eruptions, the conceivable
cause.

Statistically, the flare accumulation is highly significant.
Even when compared with the distribution of mean counts of grouped optical
flares, bootstrap resampling and randomization tests show that the probability
of a false rejection of the sceptic null hypothesis is much smaller than
0.01. Highly energetic cosmic ray flares observed between 1942 and 1970
(Sakurai, 1974)
corroborate this result. As to a potential physical background of the link
between energetic solar eruptions and ENSO events I refer to "Solar
Forcing of El Niño and La Niña"(Landscheidt,
2000 a ) and "Solar Activity Controls El Niño
and La Niña"(Landscheidt
1999 a).

NAO extrema
and phases a
and d in sunspot
cycle

The Southern Oscillation and the North Atlantic Oscillation
are comparable climate phenomena though located in different world regions.
So I adopted the working hypothesis that the NAO, if subjected to solar
forcing, would be related to the same phases of eruptional activity within
the 11-year sunspot cycle as ENSO events. To test this hypothesis, I investigated
yearly means of the NAO index covering 1825 to 2000. Jones et al.
(1997) used early
instrumental data to extend the index back to 1825. These data are
available at the Climate Research Unit of the University of East Anglia
(2001). When I
subjected the time series to 5-year moving window Gaussian kernel smoothing
(Lorczak), the
smoothed curve displayed 36 extrema (maxima and minima).
I related the dates of these NAO extrema to the respective sunspot cycles
normalized to 11 years. An analysis of the normalized positions of the
extrema within the 11-year cycle showed that just the points a,
d, a/d, and d/a, which play a major role in the relationship
with ENSO events, show a close connection with NAO extrema when the data
are shifted to offset a 1.5-year lag of the NAO maxima and minima. As to
ENSO events in the Pacific, such lags reach at most a few months. A wider
lag in the North Atlantic is acceptable as its location is far north of
the equator where El Niño and La Niña develop in a climate
with a much higher energy potential. Thermal inertia of the oceans and
marine currents may be involved.

White et al.
(1997) have shown how the oceans respond to excess insolation
caused by solar forcing and why there can be a lag of several years depending
on the length of the involved cycles of solar activity.Fig.
4 shows the result of the test.

The vertical axis indicates the frequencies with
which NAO extrema fall in bins with 0.4-year class intervals. The normalized
11-year sunspot cycle runs from maximum to maximum. Phases a, d,
and d/a are marked by triangles. Point a/d nearly coincides
with the sunspot maximum. The NAO extrema accumulate around the crucial
phases. Out of 36 maxima and minima as many as 33fall at the intervals marked by horizontal bars
at the top and a short range before and after the sunpot maximum. The total
range covers 6.3 out of 11 years.

A Pearson-test covering 2 classes (1
degree of freedom) yields the chi-square value 17.4 and P=0.00003.
The probability of a false rejection of the sceptical null hypothesis is
only one in 33333. It cannot be objected that the shift to offset the lag
manipulates the data to get a significant result. When the data are tested
without any shift, there are already non-random accumulations at similar
intervals that go beyond the significance level 0.002. This pattern only
stands out more distinctly after the shift. It should be noted that the
1.5-year shift affects the position of a in the ascending part of
the sunspot cycle much stronger than the position of d in the descending
part, as the mean length of the ascending part is only 4.3 years. To get
special manipulated results under such conditions would be extremely
difficult.

Fig. 5 shows the course of yearly NAO anomalies normalized
to the standard deviation for the period 1950 - 2000. The yearly values
were taken from the time series subjected to 5-year moving window Gaussian
kernel smoothing (Lorczak).
It can be seen in detail that the crucial phases are closely connected
with NAO extrema. The perturbation in the torque cycle (PTC)
in 1968.8, indicated by an arrow, initiated a disturbance, though different
from the ENSO pattern in Fig. 1. The connection of a and d
with NAO minima and maxima was interrupted and switched to midpoints a/d
and d/a which replaced phases a and d. Yet this change
did not last long. After a decade, the former pattern re-emerged. Though
the NAO data in Fig. 5 were not shifted, the respective extrema closely
coincide with the activity phases.

This seems to contradict the results in Fig. 4 based
on a 1.5-year shift. The explanation is that the extension of the lags
depends on the level of solar activity. From 1875 to 1945, while
the sunspot activity was low or very low, the NAO constantly lagged the
activity phases by about 1.5 years, whereas the period of high solar activity
from 1947 to 1996 seems to have accelerated the solar effect. As to eruptional
activity, solar cycle No. 22, running from 1986.7 to 1996.4, was one of
the most active, or even the strongest ever observed (Landscheidt
1999 b). The ascending part of the cycle had a very short
length of no more than 2.8 years. This could explain that during this cycle
the NAO response was accelerated to such a degree that the extrema occurred
already before points a and d. The next phase d is
to be expected in 2003.2.

NAO data and
geomagnetic aa
index

Not all strong solar eruptions have an impact on
the near-Earth environment. The effect at Earth depends on the heliographic
position of the eruption and conditions in interplanetary space. Indices
of geomagnetic activity measure the response to those eruptions that actually
affect the Earth. Mayaud's aa index (Mayaud,
1973) is homogeneous and covers a long period. So I compared
it with the NAO data. I chose the period 1953 to 2000 as I wanted to extend
the comparison to galactic cosmic rays (GCR) for which neutron measurements
are available since 1953. Figure 6 shows the result.

The blue curve represents anomalies of the aa
index, smoothed and normalized to the standard deviation like the NAO index.
The brown curve displays the NAO data. The two time series are well correlated.
The correlation coefficient is as high as r = 0.78 and explains 61% of
the variance. Though there is a well established reciprocal physical link
between the aa index and galactic cosmic rays, their correlation
coefficient for the same period is only slightly higher: r = -0.82. Bootstrap
resampling, making use of up to a million samples drawn at random from
the observed set, shows clearly that the significance of r = 0.78 is so
high that there is not even one chance in a million to falsely reject the
sceptic null hypothesis. Between 1964 and the early seventies, the
correlation is weaker than after this period. This concurs with an
intermittent phase of weaker solar activity. The sunspot maxima 1947.5,
1957.9, 1979.9, and 1989.5 were all beyond R=150, whereas the maximum 1968.9
reached only R=106. For the period of high solar activity from 1970 to
2000 the correlation coefficient for aa and NAO rises to r = 0.93.
Even the physically explained negative correlation between aa and
GCR is not as high in this period: r = -0.88. This shows again that the
level of solar activity is an important factor in the investigated relationship.

NAO index
and cosmic rays

The extent of cloud cover has a strong impact on
temperature and climate, especially over the oceans. Clouds are on average
about 10°C colder than the surface and reflect between 20 and 30 %
more sunlight. Over the oceans, 67% of the sky is cloudy and more than
half of that area densely overcast. Only 15% of the continents, however,
is thickly blanketed. Svensmark and Friis-Christensen (1997)
and Svensmark (1998)
have shown that global cloud cover over the oceans, observed by satellites,
is linked to variations in the flux of cosmic rays modulated by the solar
wind. This effect is attributed to cloud seeding by ionized secondary particles.
Stronger cosmic rays are expected to extend the cloud cover, whereas weak
cosmic rays, kept at bay by strong solar wind, go along with shrinking
clouds.

New results published by and Pallé Bagó
and Butler (2000 a, b)
and Marsh and Svensmark (2000)
restrict the relationship to low clouds. Dense sheets of stratocumulus
clouds hanging just above the oceans cool more than they heat. If such
sheets shrink, it gets warmer. The cloudiest regions are in the temperate
zones. As atmospheric temperature and pressure are related, it is imaginable
that there is a connection between cosmic ray variations, cloud cover over
the Atlantic, and the North Atlantic Oscillation. Fig. 7 shows that there
is a close correlation between cosmic rays and the NAO index.

The blue curve displays smoothed normalized anomalies
of yearly mean values of GCR data observed by the Huancayo Neutron Monitor
(Solar-Geophysical Data, 1999)
since 1953. The data are reversed to make it easier to judge the degree
of a potential negative correlation. The already investigated aa
index and cosmic rays show a negative correlation because of the shielding
effect of the solar wind driven by solar activity. The brown curve plots
the NAO data. The strong negative correlation (r = - 0.77) is obvious.
It explains 59% of the variance. Interestingly, just during the weak sunspot
cycle running from 1964 to 1976 the correlation displayed a strange pattern.
A phase reversal occurred that inverted the negative correlation temporarily
to a positive one. This changed again when the following strong sunspot
cycle developed. This feature could be of importance in attempts to find
a detailed physical explanation of the connection.

Torque cycle
in the Sun's motion, solar eruptions, and NAO extrema

I have shown that zero phases of the torque cycle
in the Sun's motion, visible in Fig. 2, are linked to ENSO events (Landscheidt,
1999 a). In view of the results with phases a
and d in the sunspot cycle, there seem to be good reasons to expect
a similar connection with the NAO. Zero phases (z), as marked in
Fig. 2, do not only comprise initial phases (blue), but also phases pi(green) initiating the second half of the
respective cycle. A growing body of evidence suggests that zero phases
in the torque cycle have an impact on weather and climate because they
go along with accumulations of energetic solar eruptions. I have tried
to draw attention to this special relationship since 1976 (Landscheidt,
1976). Fig. 8 shows a new result.

The two types of zero phases in the torque cycle
have different physical functions. They are indicated in Fig. 2 by labels
c and g. Phase c(blue)
initiates an increase in orbital momentum resulting in centrifugal motion
of the Sun away from the center of mass. Phase g(green)
starts a decrease in orbital momentum resulting in centripetal motion toward
the center of mass due to prevailing gravitation in the difference forces.
In both of these cases the zero phases start an impulse of the torque in
the Sun's motion. The different types c and g could have
different effects on the Sun's activity and solar-terrestrial interaction.
So I distinguished zero phases c and g in an investigation
into their relationship with solar eruptions.

Figure 8 shows the frequency distribution of powerful
X-class flares, already analysed in Fig. 3, within a normalized interval
from one zero phase g (z(g)), marked by a triangle, to the next
one. The normalized position of zero phase c (z(c)) in between is
also indicated by a triangle.The strong X-ray flares concentrate before
and after z(g) and around z(c). As many as 27 of the investigated
34 flares concentrate on the short intervals marked by horizontal bars
at the top comprising a total of 0.35 on the scale normalized to 1. Only
7 of the flares fall at the remaining interval of 0.65 on the unit scale.
A Pearson-test covering two classes (1 degree of freedom) yields the chi-square
value 29.5 and P = 0.00000006. The null hypothesis of no correlation is
disproved at a level of significance rarely found in such small samples.
In addition, there are aggregations around 0.25 and 0.75 on the unit scale.

This would be the normalized positions of the torque
extrema labelled e in Fig. 2. Contrary to expectation, the
concentrations of flares around phases z(g) and z(c) show
no significant difference in their frequencies in spite of their different
physical functions. Solar eruptions are caused by instability on the Sun.
It could be that they are linked to instability in the solar motion cycle.
As stated by chaos theory, instability is the characteristic mark of all
zero phases that are sites of boundary transitions from one polar quality
to the opposite one, as for instance from centrifugal force to gravitation,
or vice versa. Extrema in cycles are similar sites of instability. For
a moment the quantities involved stop to grow in the positive or negative
direction and then switch to the opposite direction. If this were crucial,
it should make no difference whether the extremum is positive or negative.
I found just this in a time series of River Po discharges linked to a torque
cycle formed by the absolute rate of change | dL/dt | in the Sun's orbital
angular momentum L (Landscheidt,
2000 b). These cycles do not run from initial phase c
to the next one, but from z to z.

The connection proved dependable, as the forecast
of a maximum of the discharges in the River Po catchment area around 2001.1,
based on an absolute extremum in the torque cycle, turned out correct (Landscheidt,
2000 d). After a protracted dry period, the predicted
wet period was initiated by severe floods in Northern Italy that began
in October 2000. The wet climate continued till spring 2001. Climate in
the Mediterranean is known to be connected with the NAO (Tomasino
and Dalla Valle, 2000). So I hypothesize that all phases
z in the torque cycle, irrespective of their different physical
background, and all extrema e, independent of their sign, show a
similar relationship with extrema in the NAO data like phases a,
d, a/d, and d/a in the sunspot cycle. Fig. 9, a reprise
of Fig. 5, confirms this working hypothesis.

As surmised, extrema e play an important role
besides zero phases z. Contrary to all other cases, phases e
and z in 1963.0 and 1967.1 are not related to well developed NAO
extrema. There are only slight disturbances in the course of the NAO curve
that indicate a tendency in the respective direction. This seems to be
related to the proximity of the perturbation PTC in 1968.8, indicated by
an arrow. Just the same happened before the preceding PTC in 1933.6.
The disturbance in the torque cycle also explains a phase shift in the
z phase 1970.5, the only exception in the otherwise consistent pattern.
Phase e in 1994.4 seems rather far from the NAO minimum 1996, but
this will be explained later when dealing with Fig. 11.

The NAO data in Fig. 9 were not shifted as they cover
a period of high solar activity. I hypothesized, however, that an investigation
of the whole data set, including long periods of weak solar activity, would
show that the NAO extrema lag z and e on average by 1.5 years
like a and d . Fig. 10 shows how the NAO extrema are distributed
within intervals g to g normalized to 1 from 1825 to 2000
when they are shifted to offset a 1.5-year lag.

As postulated, the extrema concentrate at g
and around c and e. Surprisingly, the analysis reveals that
4th harmonics of the |dL/dt|-cycle are also involved. The respective
harmonics are labelled e/c, c/e, and e/g. For short,
they will be called phases m because they appear at midpoints between
normalized phases z and e. A closer look shows that 4th harmonics
only emerge in very long z - z intervals. Between 1819.4 and 2008.4
the longest |dL/dt| cycle has a length of 14.8 years while the shortest
one has a length of 2.6 years. In the period 1950 to 2000, covered
in Fig. 9, there are no unusually long cycles. The active phases in the
g - g interval in Fig. 10 are precisely connected with the investigated
NAO extrema. The range of effectiveness around e/c, c/e,
and e/g is only half as wide as around g, c, and e.
Out of 36 NAO extrema as many as 32 fall at the ranges marked by horizontal
bars at the top of Fig. 10 covering a total range of 0.54 on the unit scale.
Only 4 extrema fall at the space in between the active phases.

A Pearson-test covering 2 classes (1
degree of freedom) yields the chi-square value 18.1 and P = 0.00002. The probability of a false rejection
of the null hypothesis is very small. If a range for the only omitted harmonic
g/e is inserted, though there is no aggregation of NAO extrema,
the chi-square value is still 16.2 with P = 0.00006.

Accumulation
effect and forecast potential

Fig. 11 shows the combined effect of z and
e(blue triangles) and of a,
d, a/d, and d/a(yellow triangles)
on NAO extrema. Obviously, maxima or minima occur when elements of the
two different sets coincide within a relatively small range. The data were
not shifted, as the period 1950 - 2000 is characterized by a high level
of solar activity. Phases m do not emerge as the intervals z
- z falling in this period are rather short, the longest one being
8.3 years.

The deep NAO minimum in 1969 is not only unusual
in so far as it goes along with a PTC disturbance and a phase reversal
in the zero phase 1970.5. Another distinguishing feature is the cluster
of three phases with e and z exceptionally close together.
Around the NAO minimum 1996, e and a are farther away from
the mark than any of the phases that indicate NAO extrema. Yet the midpoint
in between, indicated by an open triangle, coincides nearly exactly with
the NAO minimum. If this is a valid feature, another NAO extremum should
be expected around 2004.5, as indicated by an open triangle between d(2003.2) and z (2005.8)
on the right hand side of Fig. 11. Under the prevailing circumstances
the extremum will probably be a maximum.

Fig. 12, covering the years 1900 - 1950, confirms
the result shown in Fig.11 that NAO extrema occur when phases of the different
sets coincide within a small range. Nearly all single phases, indicated
by green circles, are far from maxima or minima in the NAO data. There
is only one exception. The second maximum from the left is related to a
single phase z. Yet this maximum is the smallest in the investigated
period. The decades after the disturbances PTC 1900 and PTC 1933.6 are
the only ones with emerging phases m and d/a. As stated before,
phases m only occur within long intervals z - z. In the present
case, the respective |dL/dt| cycles have lengths of 10.3 and 12.4 years.
As before PTC 1968.8, coinciding phases a and e before PTC
1933.6 are not linked to a fully developed extremum. The analysis covers
a period of solar activity that was weak or very weak up to the sunspot
minimum 1944.2. So the marks of the phases were shifted to offset
the 1.5-year lag. Only the phase close to the high sunspot maximum 1947.5
was not shifted. Taken together, the presented results show that
it is possible to develop a long-range forecast of NAO extrema.

Frequency
spectrum analysis

Most climatologists think that frequency analyses
of NAO indices - unlike ENSO - yield broad band spectra with no significant
dominant periodicities and no relationship with natural cycles. The
maximum entropy spectrum (Burg,
1975) in Fig. 13, based on raw yearly data of the NAO
index 1825 - 2000, disproves this assumption.

To avoid spectrum instability, a filter length of
40 coefficients was chosen, less than 25% of the 176 data points. The results
were checked by a Blackman-Tukey power spectrum (Blackman
and Tukey, 1959). The outstanding peak at 7.8 years nearly
exactly matches the mean length 7.86 years of the |dl/dt| cycle (z -
z) measured in the investigated period 1825 - 2000. Actually,
the interval 1819 - 2008 was chosen to cover complete cycles. The
main peak is highly significant. An acknowledged reliability test
of spectral peaks does not exist for the maximum entropy method.
It is available, however, for the Blackman-Tukey power test.

Though it allows for Markov red noise in natural
time series, the level of significance is far beyond 0.01.
The mean distance of phase d from the sunspot minimum, the beginning
of the sunspot cycle, is 6.8 years. The strong peak at 13.3 years is close
to the second sub-harmonic 13.6 years of this basic distance. The third
strong peak at 5.1 years points to the mean interval a - d of 5.
2 years. The second harmonic of the main peak 7.8 years is at 3.9 years.
It is explained by the mean distance between z and e or e
and z, which is 3.9 years. The peak at 4 years is rather close to
it. The rest of the peaks shows similar relationships. The second harmonic
of the distance of phase d from the sunspot minimum at 3.4 year
is indicated by the peak at 3.5 years. The peak at 2.9 years points
at the second harmonic 2.9 years of the distance d - a, which is
5.8 years. The distance from a/d to d/a is 5.5 years.
Its second harmonic 2.8 years is related to a peak at just this wavelength.
The last distinct peak at 2.2 years could point to the Quasi-Biennial Oscillation
with a mean length of 2.2 years, but it is also close to the mean distance
2 years separating phase m from z and e.

All of these peaks are confirmed by the Blackman-Tukey
power spectrum and turn out to be significant at least at the level 0.05.
Interestingly, the low peak at 32 years on the left hand side of Fig. 13,
the only one that points to a cycle of several decades, points at the fourth
sub-harmonic 31.4 years of the mean interval z - z represented
by the main peak. So there are solid indications that the prominent
frequency peaks are real and closely connected with the solar phases in
question.

Outlook

Taken together, the presented lines of evidence leave
little doubt that there is a solid link between solar eruptions, eruptive
phases in the 11-year sunspot cycle, zero phases and extrema in the solar
motion cycle formed by | dL/dt |, and extrema in the NAO data. This opens
up new vistas of research, as it has been a tenet of climatology that the
Northern Atlantic Oscillation is an internal process in the atmosphere-ocean
system not subjected to external forcing. Moreover, the results show
clearly that contrary to statements of the IPCC and assertions in the literature
(Tett et al., 1999)
solar forcing on climate phenomena did not fade away in recent decades.
Predictability is one of the corner stones of science. The predictive
potential of the upshot is obvious, though the patterns are not as stable
as the patterns that make it possible to predict ENSO events. An
explanation could be that El Niño and La Niña develop in
an environment with a much higher energy potential.

Admittedly, the mechanisms that create such strong
solar forcing remain poorly understood in detail. Yet this situation
is not new in the history of science. Epistemologically, the stages
of gathering data, establishing morphological relationships, and setting
up working hypotheses necessarily precede the stage of elaborated theories.
We are able already to discern simple underlying patterns in a seemingly
impenetrable thicket of data without correlations. If the fields
of solar activity and climatic change shape well and develop into full-fledged
theories, it is conceivable that the semi-quantitative model presented
here will be better understood in the new theoretical environment. The
present results are only first tentative steps in a new direction.
There are many problems that can only be solved by a joint interdisciplinary
effort of open-minded scientists.

References

Blackman,
R. B. and Tukey, J. W. (1959): The measurement
of power spectra. Dover, New York.